Space based tropospheric Doppler wind Light Detection And Ranging systems (LIDARs) are currently emerging as the method of choice for obtaining global tropospheric vertical wind profiles from low Earth orbit satellites. The European Space Agency (ESA) is planning to launch the first space based Doppler wind Light Detection And Ranging (LIDAR) system in the near future (approximately May 2011) called the Atmospheric Dynamics Mission (ADM)-Aeolus. In the United States, there is an active community, consisting of civilian agencies such as the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA); Universities (such as the University of Alabama, University of Washington, Florida State University, University of Utah); and the commercial sector (including Ball Aerospace), that is actively pursuing research with the goal of flying a tropospheric wind LIDAR in space. As early as 20 years ago, a “NASA Laser Atmospheric Wind Sounder (LAWS) Science Team” was established, which in 1994 led to the formation of the “Working Group on Space-Based Lidar Winds”. This group consists of US university researchers and scientists and engineers from US civilian government agencies. It meets twice a year for a multi-day meeting to exchange the latest results and developments, concerning space borne Doppler wind LIDAR initiatives. Research and development activities, as well as missions planned by this active community, combined with the perceived importance of meteorological measurement, which was documented in publications by agencies such as NASA, NOAA, and the National Science Foundation (NSF), foster opportunities for application, sale, and/or licensing of the present invention disclosed herein. Moreover, there is a clear military application for space based, tropospheric wind observations, as such observations will improve global and local weather forecast models and provide increased battle field environment information, critical for operations planning and systems selection.
Historically, Doppler wind LIDARs have been used to measure tropospheric winds from ground based and airborne platforms. Currently, both in Europe and the US, there are efforts to use the LIDAR technique from a space based platform (low Earth orbit satellite) to obtain global tropospheric wind speeds versus altitude observations for assimilation into weather models and other atmospheric research purposes, such as the investigation of hurricanes.
Referring to FIG. 1A and FIG. 1B, the rudimentary system components of a Doppler wind LIDAR system (such as Doppler wind LIDAR 100) generally consist of a front-end 110 having a laser 112 which can be a monochromatic laser that illuminates the atmosphere 102, a telescope 114, which collects backscattered laser light return signal(s) 130 backscattered by the atmosphere 102, and a back-end 120, including a receiver 124, which measures a Doppler shift 200 from the signal of the backscattered laser light return signal(s) 130. The time difference between a laser pulse and the detection by the receiver can be used to determine the spatial difference (range) between the LIDAR instrument and where the scattering of the laser signal occurred in the atmosphere. The backscattered laser light return signal(s) 130 typically consists of two components which originate from atmospheric gas molecules 108 and atmospheric aerosols 106. Due to the large mass difference between atmospheric gas molecules 108 and atmospheric aerosols 106 that are in thermodynamic equilibrium and the resulting difference in the velocity distribution of the scatterers, the spectral width of the backscattered line is much larger for the molecular backscattering than the signal originating from the scattering of the aerosol particles. In addition to this line broadening, the bulk motion of the atmosphere 102 along the direction of the laser beam (line of sight) causes the Doppler shift 200 of the backscattered laser light return signal(s) 130, which is equivalent to the line of sight wind speed, see FIG. 1B, which illustrates a sketch of the involved spectra.
Referring again to FIG. 1B, this illustration, from Endeman [2006], shows the signal from the monochromatic laser, such as the laser 112, and the superimposed backscattered laser light return signal(s) 130, consisting of the molecular scattering (Rayleigh Signal 132) and aerosol scattering (Mie Signal 134) for a near ultra violet (UV) Doppler wind LIDAR such as the Doppler wind LIDAR 100 illustrated in FIG. 1A, contemplating the ADM Aeolus mission of the European Space Agency. Rayleigh scattering theory (named after the British physicist Lord Rayleigh) describes the elastic scattering of electromagnetic radiation by particles much smaller than the wavelength of the light, such as atmospheric gas molecules 108. Mie scattering theory (named after the German physicist Gustav Mie) describes the scattering and absorption of electromagnetic radiation by spherical particles of any size (such as idealized atmospheric aerosols 106) through solving the Maxwell equations.
The spectral widths given in FIG. 1B are expressed in corresponding velocity units. Note that the absolute intensity of the outgoing signal of the laser 112 is many times larger than the return signal (such as the Rayleigh Signal 132 of the backscattered laser light return signal(s) 130).
Again referring to FIG. 1B, the determination of the Doppler shift 200 of both the molecular and aerosol backscattering signals is performed using either a direct (incoherent) detection system or a heterodyne (coherent) detection system, depending primarily on the spectral width of the return signal and the signal wavelength (see Rocadenbosch, 2003 or Pfaffrath, 2006).
Referring again to FIG. 1B, the current state of the art techniques include coherent detection methods that are based on mixing the atmospheric signal with a local oscillator signal that is slightly offset in frequency from a LIDAR laser signal and the subsequent amplification and detection of the difference signal. This technique is typically used for the detection of the spectrally narrow aerosol backscatter signal, such as the Mie Signal 134. Incoherent techniques, i.e., the direct detection techniques, can be used for both the aerosol backscattering signals (i.e., Mie Signal 134) and the molecular backscattering signals (such as the Rayleigh Signal 132), where the molecular backscattering signals have a much broader spectral width due to the higher thermal velocity of the molecules. These techniques include edge detection with filters and fringe detection techniques. Edge detection filters are typically Fabry Perot interferometers, which have high surface tolerance requirements and are difficult to align and to keep aligned in rough thermal and mechanical environments. Fringe imaging techniques also use Fabry Perot interferometers, but Fizeau interferometers, and Stepped Fourier Transform Spectrometer or stepped FTS (which includes Optical Autocovariance Wind LIDAR (OAWL)) can also be employed.
In the heterodyne (coherent) detection system, the return signal is combined with the outgoing signal of the laser 112, and that outgoing signal is shifted by an additional amount (also called: an intermediate frequency). This allows the determination of the magnitude and sign of the Doppler shift 200 from the detected difference signal, which is the sum of the intermediate frequency and the Doppler shift 200 component. Heterodyne detection systems are generally used for narrow band return signals, such as aerosol scattering signals (i.e., Mie Signal 134).
Referring to FIG. 2, edge detection techniques incorporate a spectral filter placed at one steep edge of the returned spectral line, where a small line shift results in a large change of the signal transmitted by the filter.
Referring again to FIG. 2, improved edge detection techniques incorporate two spectral filters. A first spectral filter B 206 (TB(I) is placed on a red edge of the return line and a second spectral filter A 204 (TA(I) is placed on the blue edge of the return line, where a ratio of the filtered signals can be used to determine the Doppler shift 200.
Again referring to FIG. 2, (contrasting transmission intensity in arbitrary units (a.u.) with wavelength in picometers (pm)), typically, Fabry-Perot type interferometers are used as the spectral filters in the edge detection techniques, where the edge detection techniques are generally used for molecular scattering signals, due to the difficulty of manufacturing narrow enough filters for the much narrower aerosol signals. FIG. 2 illustrates a typical spectral filter arrangement for the two filter detection technique, such as filter A 204 (TA(I)) and filter B 206 (TB(I)) (also known as the double edge detection technique). Filter A 204 (TA(I)) and filter B 206 (TB(I)) can both be dielectric interference filters.
Referring again to FIG. 2, this illustration, taken from Pfaffrath [2006], shows the atmospheric return signal, such as the backscattered laser light return signal(s) 130 for zero wind speed and a finite wind speed as well as the transmittance functions of the two edge spectral filters A 204 (TA(I)) and B 206 (TB(I)). The ratio of the signals transmitted by the two edge spectral filters A 204 (TA(I)) and B 206 (TB(I)) contains the line position information.
Referring to FIG. 2, FIG. 4 and FIG. 5, determining the Doppler shift 200 of the aerosol signal with a direct detection system (also known as the incoherent detection system) includes fringe imaging by an array detector, such as an array detector 410, see FIG. 4 and FIG. 5. Exemplary embodiments include imaging a Fabry Perot ring pattern, which contains the line position information in the radius of the ring (transmittance angle) on an array detector, and/or imaging the straight fringe(s) formed by a Fizeau interferometer, which carry the line position information in their lateral position.
The ESA ADM Aeolus mission, incorporating the first space borne Doppler wind LIDAR, uses a Fizeau interferometer for the aerosol signal (Mie Signal 134) and a double Fabry-Perot interferometer, such as filter A 204 and/or filter B 206 (see FIG. 2) to perform edge detection on the molecular signal (Rayleigh Signal 132).
In addition to the detection systems described above, a new type of direct detection concept is currently being developed in the US by Ball Aerospace & Technologies Corp. It is called Optical Autocovariance Wind LIDAR (OAWL) and is supported by NASA. The OAWL concept is based on imaging four phases of a fringe (0, π/2, π, 3π/2) created by a Mach-Zehnder-like interferometer. This concept is, in principle, similar to a phase-stepped Michelson concept previously used for passive measurement of upper and middle atmospheric winds by the Wind Imaging Interferometer (WINDII) on NASA's Upper Atmosphere Research Satellite (UARS). However, OAWL has some distinct differences to the WINDII approach, for example OAWL has no moving optical parts; and it measures all four phase points simultaneously [Grund, 2009].
FIG. 3 illustrates a typical optical autocorrelation function (OACF) or interferogram versus the optical path difference (OPD) and the four phase points that are sampled by the OAWL technique.
Referring again to FIG. 3, the interferogram of a return signal consisting of a spectrally wide molecular contribution and a spectrally narrow aerosol contribution is illustrated by the traveling wave extending across FIG. 3. The rapidly decaying envelope function at low OPD originates from the wide line returning from the molecular scattering. The fringes for the higher OPD originate from the narrow aerosol signal. The inserts illustrate the four phase points sampled simultaneously by the OAWL approach for zero wind and the Doppler shifted atmospheric return (Figure from: Grund et al., 2009).
Referring to FIG. 4, and FIG. 6, independent of any Doppler wind LIDAR activities, the US Naval Research Laboratory (NRL) and St. Cloud State University have developed an optical technique to passively measure middle and upper atmospheric winds using the Doppler shift of naturally occurring atmospheric emission lines (herein “Doppler Shifted Emission 602”) associated with atmospheric gas molecules 108 and/or atmospheric atoms 604 (see the DOPPLER WIND INSTRUMENT 600, illustrated in FIG. 6), rather than LIDAR backscattered laser light return signal(s) 130 (see FIG. 1A). The concept of this optical technique to passively measure middle and upper atmospheric winds is called DOPPLER ASYMMETRIC SPATIAL HETERODYNE SPECTROSCOPY (DASH) (herein “DASH 400”) and has been proven in the laboratory and is disclosed in issued U.S. Pat. No. 7,773,229, discussing various embodiments including using a Koesters prism.
Referring to FIG. 4, a field-widened DASH 400 technique potentially provides a throughput (sensitivity) advantage over conventional techniques in addition to the robustness, compactness, and the fact that it does not need moving optical parts. A major difference of DASH 400, when compared to the other fringe imaging techniques, is that it can simultaneously detect many hundred phase samples and a number of fringes; according to exemplary embodiments, typically 512 phase samples and 40-200 fringes.
Referring again to FIG. 4, DASH 400 can be built in a compact, robust way, which makes it suitable for space flight, because the DASH 400 concept does not require any moving optical parts and thus does not require routine realignment of optical components. Furthermore, DASH 400 exhibits large Etendue (Sensitivity): As exhibited by the phase-stepped Michelson interferometer (also termed Stepped Fourier Transform Spectrometer or stepped FTS), DASH 400 can be field widened to enhance interferometric throughput.
Again referring to FIG. 4, in addition DASH 400 exhibits increased immunity to ghosts and background features: Since DASH 400 records several hundred interferogram points within an optical path difference interval centered on a path offset, DASH 400 implementations provide increased immunity to interferometer ghost fringes, effects of laser mode hopping and background signal features which are more difficult to identify if only four or eight phase points are available.
Referring again to FIG. 4, thermal drifts: Just as for stepped FTS, Fizeau and Fabry Perot interferometers, thermal effects on the measured phase are expected to be significant. To mitigate these thermal effects the interferometer can be designed using materials that provide maximum thermal compensation, as has been successfully demonstrated for stepped FTS (Thuillier and Shepherd, 1985; Thuillier and Herse, 1991). Additionally, DASH 400 allows for simultaneous phase tracking, because the large number of interferogram samples (typically 40-200) causes the simultaneous phase tracking of additional calibration lines (Englert et al., 2007). Using a two dimensional array detector, such as the array detector 410, facilitates tracking the unshifted laser line and the atmospheric signal simultaneously on different parts (rows) on the array detector 410 (see FIG. 4).
However, there are no known space based systems and/or methods of achieving tropospheric wind observations for obtaining global tropospheric vertical wind profiles, accomplished by using a Doppler Asymmetric Spatial Heterodyne Spectroscopy (DASH) interferometer as a direct detection system of a Doppler wind Light Detection and Ranging (LIDAR) receiver/instrument, in a manner equivalent to determining the line of sight wind speed with the LIDAR observation by measuring the frequency shift caused by winds, i.e., the Doppler shift of a return signal from a Doppler wind LIDAR.
Therefore, the need exists for systems and methods of obtaining global tropospheric vertical wind profiles, accomplished by using a Doppler Asymmetric Spatial Heterodyne Spectroscopy interferometer as a direct detection apparatus of a Doppler wind Light Detection and Ranging (LIDAR) receiver/instrument.
Furthermore, the need exists for space based systems and/or methods of achieving tropospheric wind observations for obtaining high precision global tropospheric vertical wind profiles, using a robust suite of stationary optical components.